Robust Adaptively Unscented Particle Filtering Method on Dynamic Attitude Measurement for Steering Drilling

Real-time measurement of down-hole dynamic space attitude parameters is a prerequisite for real-time guidance control for drilling tools. In drilling engineering, the dynamic attitude measurement is seriously disturbed by the well condition, well temperature and vibration of guide drill, which causes the attitude parameters to be distorted seriously, which leads to the inaccuracy of attitude parameter measurement. This paper presents a new method of dynamic attitude measurement based on Robust Adaptively Unscented Particle Filtering Method. The influence of vibration of drill tool on dynamic attitude measurement is effectively filtered by using the equivalent weight function and adaptive factor to distribute information. Simulation experiments and real drilling data tests show that the algorithm can filter out the interference signal of the guide drilling tool, and can effectively improve the dynamic measurement accuracy of the attitude parameters.